Description:

How can we explore the spatial distribution of poverty and determine its correlates? This exercise examines data from Sri Lanka. Many quantitative studies use ordinary least squares (OLS) regression to estimate the effect of variables such as ethnicity, proximity to urban areas, elevation, and other indicators of development on poverty rates. This exercise uses a more generalized geographically weighted regression (GWR) model in addition to the OLS model to incorporate the effects of spatial clustering.
Keywords: poverty estimation; development studies; South Asia; Sri Lanka; Ordinary Least Squares (OLS) Regression; Weight Matrices; Weight functions; local and global multicollinearity; Geographically Weighted Regression (GWR)